Tuesday, August 26, 2025

Nvidia's robot brain πŸ€–, Google fights sideloading πŸ“±, against prediction markets πŸ“ˆ 

Nvidia's Jetson AGX Thor robotics chip module is now on sale for $3,499 as a developer kit. The first kits will ship next month ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌  ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ 

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TLDR 2025-08-26

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Big Tech & Startups

Nvidia's new 'robot brain' goes on sale for $3,499 as company targets robotics for growth (3 minute read)

Nvidia's Jetson AGX Thor robotics chip module is now on sale for $3,499 as a developer kit. The first kits will ship next month. The chips will allow customers to create robots that run generative AI models. They can also be used for self-driving cars. The Jetson Thor chips are based on Nvidia's Blackwell graphics processor, which is also used in the company's current generation of AI chips and chips for computer games.
Google will block sideloading of unverified Android apps starting next year (5 minute read)

Google has announced plans to begin verifying the identities of all Android app developers, no matter where they offer their content. Apps without verification will stop working on most Android devices in the coming years. The company plans to create a streamlined Android Developer Console that devs can use if they plan to distribute apps outside of the Play Store. Google won't check the content or functionality of apps outside of the Play Store.
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Science & Futuristic Technology

UltraRAM scaled for volume production (4 minute read)

UltraRAM promises DRAM-like speeds, 4,000x the durability of NAND, and data retention for up to a thousand years. Quinas Technology and IQE have successfully developed a scalable process for producing UltraRAM. The companies are now weighing pilot production with various foundries and other collaborators.
Building Ultra Cheap Energy Storage for Solar PV (32 minute read)

Standard Thermal is a company that aims to make energy from solar PV available at all times at a price that is competitive with US natural gas. The company's technology works by storing energy as heat in large piles of dirt. Electric heating elements embedded in the dirt convert electricity to heat, and pipes carrying fluid remove the heat to supply customers. The capital cost is comparable to natural gas storage at less than $0.10 per kilowatt-hour thermal and a thousand times cheaper than batteries. Standard Thermal's system can provide hundreds of megawatts of thermal demand as long as land is available.
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Programming, Design & Data Science

FastMCP: Deploy a remote MCP server with auth from a GitHub repo in 60 seconds (Sponsor)

FastMCP Cloud is here with production-ready AI infrastructure that just works. From the team behind FastMCP, instantly deploy your MCP servers as remote, authenticated endpoints for use with Claude, Cursor, or your favorite LLM. Get started for free or check out the open source project
Wicked Python trickery - dynamically patch a Python function's source code at runtime (17 minute read)

It's possible to dynamically change a function's source code at run time in Python using the compile and exec functions. This technique enables developers to build more flexible AI bots that can generate and execute code with access to the current environment. However, it also raises some serious security concerns. This post walks readers through how the technique works and the real security concerns with using the approach.
Prediction-Encoded Pixels (GitHub Repo)

Prediction-Encoded Pixels is a format specifically designed for low-color pixel art. It uses 'Prediction by Partial Matching, Order-2' compression, which is able to compress packed-palette-indices smaller than GIF, PNG, and QOI. It's two to 10 times slower than GIF/PNG/QOI, depending on the image, but it often compresses images 20% to 50% smaller than GIF/PNG, and multiple times smaller than QOI. The format is still in an experimental phase.
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Miscellaneous

Predicting our own demise (13 minute read)

Prediction markets don't provide better predictions about the future. The best, most efficient financial markets have standardized products, many participants, low transaction costs, and heterogeneous participants. Prediction markets lack participants with heterogeneous risk preferences. It's also possible for participants to manipulate some outcomes. Prediction markets are bad market design, and they induce bad incentives, so we should put the genie back in the box while there's still time.
Inside Intel's Tricky Dance With Trump (15 minute read)

President Donald Trump told Lip-Bu Tan, Intel's chief executive, to step down five months into his tenure because of his past ties to the Chinese military. Tan eventually smoothed things over with Trump, but at a cost: in return for his support, the administration converted nearly $9 billion in grants promised to Intel as part of the 2022 Chips Act into a 10% equity stake in the company. The US government is now Intel's biggest shareholder. Tan still needs to resolve core business challenges to get Intel back on track. Without new commitments from customers, converting government grants to stock will only leave the company in a worse financial shape by diluting shareholders.

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The Simple Truth About MCPs (3 minute read)

MCPs make your AI run other people's prompts, and those prompts send you to other people's code.
My Current AI Dev Workflow (4 minute read)

A combination of Ghostty, Claude Code, and minimal tooling results in maximum productivity.
Apple's retreat from live sports (4 minute read)

Apple is ending its 'Friday Night Baseball' partnership with MLB after the 2025 season due to low viewership, high costs, and fan frustration with fragmented streaming access.
On meetings (3 minute read)

Meetings are expensive, so people should default to asynchronous communication.
The Bubble That Knows It's a Bubble (25 minute read)

The sequence of 'revolutionary technology, abundant capital, speculative frenzy, and sudden reality checks' has played out with remarkable consistency for over 180 years.
Ex-Employee Sentenced to 4 Years for Sabotaging Company's Computer Network (4 minute read)

David Lu, who worked for Eaton Corporation, wrote malicious code that crashed the company's network after a corporate realignment reduced his job responsibilities and restricted his access to certain servers.

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